gov.sandia.cognition.statistics.distribution

Class UniformDistribution.CDF

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.AbstractDistribution<NumberType>

gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution<java.lang.Double>

gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution

gov.sandia.cognition.statistics.distribution.UniformDistribution

gov.sandia.cognition.statistics.distribution.UniformDistribution.CDF

All Implemented Interfaces:

Evaluator<java.lang.Double,java.lang.Double>, ClosedFormDifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>, DifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>, Vectorizable, ScalarFunction<java.lang.Double>, UnivariateScalarFunction, ClosedFormComputableDistribution<java.lang.Double>, ClosedFormCumulativeDistributionFunction<java.lang.Double>, ClosedFormDistribution<java.lang.Double>, ClosedFormUnivariateDistribution<java.lang.Double>, ComputableDistribution<java.lang.Double>, CumulativeDistributionFunction<java.lang.Double>, Distribution<java.lang.Double>, DistributionWithMean<java.lang.Double>, EstimableDistribution<java.lang.Double,UniformDistribution>, InvertibleCumulativeDistributionFunction<java.lang.Double>, SmoothCumulativeDistributionFunction, SmoothUnivariateDistribution, UnivariateDistribution<java.lang.Double>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

UniformDistribution

public static class UniformDistribution.CDF
extends UniformDistribution
implements SmoothCumulativeDistributionFunction, InvertibleCumulativeDistributionFunction<java.lang.Double>

Cumulative Distribution Function of a uniform

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class gov.sandia.cognition.statistics.distribution.UniformDistribution

UniformDistribution.CDF, UniformDistribution.MaximumLikelihoodEstimator, UniformDistribution.PDF

Field Summary

Fields inherited from class gov.sandia.cognition.statistics.distribution.UniformDistribution

DEFAULT_MAX, DEFAULT_MIN

Constructor Summary

Constructors

Constructor and Description
CDF() Creates a new instance of CDF
CDF(double minSupport, double maxSupport) Creates a new instance of CDF
CDF(UniformDistribution other) Copy constructor

Method Summary

Modifier and Type	Method and Description
UniformDistribution.CDF	clone() This makes public the clone method on the Object class and removes the exception that it throws.
java.lang.Double	differentiate(java.lang.Double input) Differentiates the output with respect to the input
double	evaluate(double input) Produces a double output for the given double input
java.lang.Double	evaluate(java.lang.Double input) Evaluates the function on the given input and returns the output.
static double	evaluate(double input, double minSupport, double maxSupport) Evaluates the Uniform(minSupport,maxSupport) CDF for the given input
double	evaluateAsDouble(java.lang.Double input) Evaluates the scalar function as a double.
UniformDistribution.CDF	getCDF() Gets the CDF of a scalar distribution.
UniformDistribution.PDF	getDerivative() Gets the closed-form derivative of the function.
java.lang.Double	inverse(double probability) Computes the inverse of the CDF for the given probability.

Methods inherited from class gov.sandia.cognition.statistics.distribution.UniformDistribution

convertFromVector, convertToVector, getEstimator, getMaxSupport, getMeanAsDouble, getMinSupport, getProbabilityFunction, getVariance, sample, sampleInto, setMaxSupport, setMinSupport

Methods inherited from class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution

getMean, sampleAsDouble, sampleAsDoubles, sampleInto

Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution

sample

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.statistics.SmoothUnivariateDistribution

getMean, getProbabilityFunction, sampleAsDouble, sampleAsDoubles, sampleInto

Methods inherited from interface gov.sandia.cognition.statistics.UnivariateDistribution

getMaxSupport, getMeanAsDouble, getMinSupport, getVariance

Methods inherited from interface gov.sandia.cognition.statistics.Distribution

sample, sample, sampleInto

Methods inherited from interface gov.sandia.cognition.math.matrix.Vectorizable

convertFromVector, convertToVector

Constructor Detail

CDF

public CDF()

Creates a new instance of CDF

CDF

public CDF(double minSupport,
           double maxSupport)

Creates a new instance of CDF

Parameters:

minSupport - Minimum x bound on the distribution

maxSupport - Maximum bound on the distribution

CDF

public CDF(UniformDistribution other)

Copy constructor

Parameters:

other - UniformDistribution to copy

Method Detail

clone

public UniformDistribution.CDF clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:

clone in interface Vectorizable

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class UniformDistribution

Returns:

A clone of this object.

evaluate

public double evaluate(double input)

Description copied from interface: UnivariateScalarFunction

Produces a double output for the given double input

Specified by:

evaluate in interface UnivariateScalarFunction

Parameters:

input - Input to the Evaluator

Returns:

output at the given input

evaluate

public java.lang.Double evaluate(java.lang.Double input)

Description copied from interface: Evaluator

Evaluates the function on the given input and returns the output.

Specified by:

evaluate in interface Evaluator<java.lang.Double,java.lang.Double>

Specified by:

evaluate in interface ScalarFunction<java.lang.Double>

Specified by:

evaluate in interface UnivariateScalarFunction

Parameters:

input - The input to evaluate.

Returns:

The output produced by evaluating the input.

evaluateAsDouble

public double evaluateAsDouble(java.lang.Double input)

Description copied from interface: ScalarFunction

Evaluates the scalar function as a double.

Specified by:

evaluateAsDouble in interface ScalarFunction<java.lang.Double>

Specified by:

evaluateAsDouble in interface UnivariateScalarFunction

Parameters:

input - The input value.

Returns:

The scalar output calculated from the given input.

evaluate

public static double evaluate(double input,
                              double minSupport,
                              double maxSupport)

Evaluates the Uniform(minSupport,maxSupport) CDF for the given input

Parameters:

minSupport - Minimum x bound on the distribution

maxSupport - Maximum x bound on the distribution

input - Input to evaluate the CDF at

Returns:

Uniform(minSupport,maxSupport) CDF evaluated at input

getCDF

public UniformDistribution.CDF getCDF()

Description copied from interface: UnivariateDistribution

Gets the CDF of a scalar distribution.

Specified by:

getCDF in interface ClosedFormUnivariateDistribution<java.lang.Double>

Specified by:

getCDF in interface SmoothUnivariateDistribution

Specified by:

getCDF in interface UnivariateDistribution<java.lang.Double>

Overrides:

getCDF in class UniformDistribution

Returns:

CDF of the scalar distribution.

getDerivative

public UniformDistribution.PDF getDerivative()

Description copied from interface: ClosedFormDifferentiableEvaluator

Gets the closed-form derivative of the function.

Specified by:

getDerivative in interface ClosedFormDifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>

Specified by:

getDerivative in interface SmoothCumulativeDistributionFunction

Returns:

Closed-form derivative of the function.

differentiate

public java.lang.Double differentiate(java.lang.Double input)

Description copied from interface: DifferentiableEvaluator

Differentiates the output with respect to the input

Specified by:

differentiate in interface DifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>

Parameters:

input - Input about which to compute the derivative

Returns:

Derivative of the output with respect to the given input

inverse

public java.lang.Double inverse(double probability)

Description copied from interface: InvertibleCumulativeDistributionFunction

Computes the inverse of the CDF for the given probability. That is, compute the value "x" such that p=CDF(x).

Specified by:

inverse in interface InvertibleCumulativeDistributionFunction<java.lang.Double>

Parameters:

probability - Probability to invert.

Returns:

Inverse of the CDF for the given probability.